Deer exclusion unveils abiotic filtering in forest understorey plant assemblages
Bibliographic record
Abstract
BACKGROUND AND AIMS: The role of deer (family Cervidae) in ecosystem functioning has traditionally been neglected by forest ecologists due to the animal's scarcity in most parts of the northern hemisphere. However, the dramatic rebound in deer populations throughout the 20th century has brought deer browsing to the forefront of forest ecological questioning. Today there is ample evidence that deer affect tree regeneration, understorey plant and animal diversity, and even litter decomposition. However, the mechanisms underlying the effects of deer on forest ecosystems remain unclear. Among others, the relative role of abiotic factors versus biotic interactions (e.g. herbivory) in shaping plant assemblages remains largely unknown. METHODS: We used a large-scale experiment with exclosures distributed along abiotic gradients to understand the role of black-tailed deer (Odocoileus hemionus sitchensis) on the forest understorey on the Haida Gwaii archipelago (western Canada), a unique context where most of the key ecological effects of deer presence have already been intensively studied. KEY RESULTS: Our results demonstrate that 20 years of deer exclusion resulted in a clear increase in vascular plant richness, diversity and cover, and caused a decline in bryophyte cover. Exclusion also unveiled abiotic (i.e. soil water availability and fertility) filtering of plant assemblages that would otherwise have been masked by the impact of abundant deer populations. However, deer exclusion did not lead to an increase in beta diversity, probably because some remnant species had a competitive advantage to regrow after decades of over browsing. CONCLUSIONS: We demonstrated that long-term herbivory by deer can be a dominant factor structuring understorey plant communities that overwhelms abiotic factors. However, while exclosures prove useful to assess the overall effects of large herbivores, the results from our studies at broader scales on the Haida Gwaii archipelago suggest that exclosure experiments should be used cautiously when inferring the mechanisms at work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".